Interface Design for Early Detection and Improvement of Age-Related Changes for Fall and Prevention
| Project/Area Number |
18K17712
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| Research Category |
Grant-in-Aid for Early-Career Scientists
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| Allocation Type | Multi-year Fund |
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| Review Section |
Basic Section 59010:Rehabilitation science-related
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| Research Institution | Tamagawa University (2019-2022)
Tokyo Institute of Technology (2018) |
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Principal Investigator |
MUTO Yumiko 玉川大学, 脳科学研究所, 准教授 (30614614)
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| Project Period (FY) |
2018-04-01 – 2023-03-31
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| Project Status |
Completed (Fiscal Year 2022)
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| Budget Amount *help |
¥3,510,000 (Direct Cost: ¥2,700,000、Indirect Cost: ¥810,000)
Fiscal Year 2020: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2019: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2018: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
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| Keywords | 福祉工学 / ヒューマンインタフェース / 加齢 / 高齢者 / 姿勢 / 健康維持 / AI / 転倒予防 / 介護予防 / 転倒・事故リスク / 時系列解析 |
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| Outline of Final Research Achievements |
We examined the relationship between changes in posture and aging and showed that the impact of aging was more prominent while in motion than at rest. Furthermore, by surveying posture, age, sex, bone density, height, weight, body fat, left- and right-arm strengths, leg strength, and the history of falls in 272 people with ages of 65 years or older, we showed that there were individual differences in their health, muscle strength, and body fat and that posture parameters can be used to classify their health status. Moreover, we showed that the impact of aging on posture is more prominent during motion, such as while walking and standing, than when at rest, with a tendency to tilt forward. Based on these findings, our study focused on individual differences in the health status of elderly people and proposed a technique to improve postures by using MR(mixed reality).
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| Academic Significance and Societal Importance of the Research Achievements |
従来の姿勢の改善については、静止時の脊柱の湾曲度合いを計測し、その結果に基づき助言を行う手法が一般的であった。また、静止時の姿勢の計測結果に基づき、動作時の姿勢の改善へつなげることは難しい。さらに、実環境における歩行などの動作時には、安全な動作のために、周囲や外乱に向けて注意を向ける必要もあり、動作中に意識的に姿勢改善を行いつつ、外乱等に対応していくことは、ユーザに負荷をかけるとともに、安全性が懸念される。提案されたMR技術を用いた姿勢改善技術は、これらの課題を解決し、個人差に対応しつつ、投影された自己の姿勢を視認しながら、歩行など自由な動作における個々の姿勢特性を可視化することができる。
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Report
(6 results)
Research Products
(22 results)
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[Presentation] Evaluation Method of Subjective Sleep Satisfaction by Measurement of Body Movement2021
Author(s)
Muto, T., Akitaya, Y., Nishimura, A., Orikasa, A., Kurita, K., Miyasaka Y., Ishiwata, J., and Muto, Y.
Organizer
BIOCAS2021
Related Report
Int'l Joint Research
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[Presentation] Correction of Slouching Waking Posture by Laser Pointer and Virtual Pointer Tasks2021
Author(s)
Muto,T., Murata S., Suzuki A., Fukumoto, M., Onuma, T., Suzuki, Y., Jeong S., Hanita S. and Muto Y.
Organizer
STSS2021
Related Report
Int'l Joint Research
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